Shock Propagation within Multisector Firms
What this paper finds — and why it matters
Layer 1: Overview
This paper documents a novel channel through which trade shocks propagate across industries: the internal networks of U.S. multisector firms (the working paper circulated as “Import Competition and Firms’ Internal Networks”). The motivation is that prior China-shock research traced effects through input-output networks and agglomeration but overlooked multisector firms, which account for 71% of total U.S. manufacturing employment and 25% of overall U.S. employment. When a firm owns establishments in several industries with differing exposure to Chinese import competition, it is ex ante ambiguous whether an unexposed plant gains (worker reallocation toward it), loses (dampened firm-level production from complementarities or financial constraints), or is unaffected (independent plants).
Data: the Longitudinal Business Database (LBD), the Census administrative panel covering the universe of non-farm establishments with at least one paid employee. The sample is multisector firms operating at least one manufacturing establishment, including both manufacturing and non-manufacturing plants, restricted to establishments active in 1991; main period 1991-2007 (pre-trend window 1976-1991). The core sample has roughly 573,000 establishments and 62,000 firms. The average firm has 427 workers (median 22), operates in 3 SIC-4-digit sectors, and has 9 establishments (2 manufacturing, 7 non-manufacturing); over half of establishments exited during 1991-2007.
Strategy: direct China shock is industry-level growth in Chinese import penetration 1991-2007 (Acemoglu-Autor-Dorn-Hanson-Price measure). The key new variable, the “indirect shock,” is an employment-share-weighted average of direct China shocks hitting the firm’s OTHER industries (own industry excluded). Both shocks are instrumented using Chinese import penetration into eight other high-income countries (following Autor et al. 2014). Dependent variable is the Davis-Haltiwanger-Schuh arc-growth rate of establishment employment (bounded -2 to 2). Regressions are weighted by initial employment with county and SIC-2- or SIC-4-digit industry fixed effects; standard errors two-way clustered by state and firm.
Main findings: both direct and indirect shocks significantly reduce establishment employment growth at the 1% level. The indirect effect is an order of magnitude stronger - an interdecile increase in the indirect shock lowers the arc-growth rate by 0.126 (= -0.166 x 0.759), roughly 12 times the 0.011 reduction from an interdecile direct shock (OLS Table 2 col 2). IV estimates are larger: direct coefficient about -0.102 to -0.108, indirect about -0.131 to -0.208 (Table 3). The effect operates primarily through the extensive margin (establishment exit), not the intensive margin; the entry margin is statistically and economically insignificant. The shock spills over both across manufacturing industries within a firm (manufacturing-only indirect coefficient about -0.13 to -0.18) and from manufacturing to non-manufacturing establishments (non-manufacturing indirect coefficient between -0.25 and -0.135). The effect accumulated mainly during the 1990s and stabilized after 2001. Mechanisms: plants that use inputs from sister establishments respond more strongly (within-firm downstream linkages); firms with wider scope absorb the shock more easily; larger establishments respond more. No support for upstream-supply linkages, capital/skill intensity, firm size, or financial-constraint channels. At the sector level, the indirect shock significantly lowers manufacturing employment growth (indirect coefficient about -0.747, significant at 10%; exit margin significant at 1%), so spillovers survive aggregation.
Layer 2: Deep Dive
What is the identification strategy and what are the main threats to it?
Each establishment’s direct exposure is its SIC-4-digit industry’s growth in Chinese import penetration 1991-2007 (numerator = change in real U.S. imports from China; denominator = 1991 domestic absorption). The indirect shock is the 1991-employment-share-weighted average of direct shocks in the firm’s OTHER industries, excluding the establishment’s own industry. To purge U.S. demand-driven import growth, both shocks are instrumented by Chinese import penetration into eight other high-income countries (Australia, Denmark, Finland, Germany, Japan, New Zealand, Spain, Switzerland). Threats addressed: (1) selection/pre-existing trends - a pretrend test on 1976-1990 employment growth shows no relationship (coefficient -0.013, insignificant); (2) the indirect effect could reflect connectedness to sectors in general rather than the firm’s specific sectors - a placebo test randomizing sister-establishment sector affiliations over 500 draws yields an insignificant placebo indirect coefficient (-0.001); (3) a common clustered shock hitting all of a firm’s industries - direct and indirect shocks (and their IVs) show no significant correlation; (4) demand-shock correlation across countries - results hold when dropping computer, construction, and apparel industries.
What are the main mechanisms and how are they distinguished empirically?
Mechanisms are tested via heterogeneous treatment effects (Table 7), interacting the indirect shock with firm/establishment characteristics under SIC-4-digit FE. Within-firm trade: a ‘Use=1’ dummy (establishment’s industry uses inputs from sister establishments’ industries, from BEA I-O tables) significantly amplifies the indirect effect (interaction -0.090, significant at 5%), consistent with downstream plants losing relation-specific production; a ‘Supply=1’ dummy (upstream linkage) is insignificant. Economies of scope: interactions with number of SIC-4 sectors and with 1-minus-HHI are both significant at 5% and positive (wider scope cushions the shock). Establishment size: larger plants respond more strongly to the indirect shock (significant), rationalized via Holmes-Stevens - large plants make standardized goods facing fierce Chinese competition - but firm size is insignificant.
What heterogeneity is documented?
Spillovers occur both across manufacturing industries within a firm and from manufacturing to non-manufacturing establishments, with similar magnitudes (manufacturing indirect coefficient about -0.13 to -0.18; non-manufacturing about -0.135 to -0.25). Effects are stronger for establishments using inputs from sister plants, weaker for firms with broader scope, and stronger for larger establishments. Effects accumulated mainly in the 1990s and stabilized after 2001; subperiod analysis confirms the indirect shock was much stronger in 1991-1999 (indirect coefficient about -0.27 to -0.50) than 1999-2007.
What robustness checks are run?
Pretrend test (1976-1990, no trend); placebo random networks (500 draws, insignificant); no direct-indirect shock correlation; disaggregated industry FE up to SIC-8-digit using NETS data (indirect coefficient stays about -0.063 to -0.065, significant at 1%); controlling for other-sector within-firm characteristics (log wages, wage and employment-share growth 1976-1991); shift-share robust standard errors following Adao et al. 2019 (which are smaller than the two-way-clustered baseline); dropping outliers by firm size and by indirect-shock deciles; dropping affiliation and industry switchers; dropping demand-shock-prone industries (computer/construction/apparel); an alternative weight using only manufacturing employment in the denominator; unweighted regressions; and an entry-margin augmentation (entry remains insignificant, exit dominates).
How does this paper relate to and differ from closely related prior work?
It builds on the China-shock literature (Autor-Dorn-Hanson 2013; Acemoglu et al. 2016; Pierce-Schott 2016; Asquith et al. 2019) but introduces within-firm sectoral networks as a new propagation channel, arguing the China shock’s impact may be larger than previously estimated. It extends the firm-internal-network literature (Giroud-Mueller 2019; Hyun-Kim 2020 on regional shocks; Cravino-Levchenko 2017 and Boehm et al. 2019 on cross-country shocks) to sector-level shocks. Versus Ding (2020), who studies manufacturing multi-industry firms with at least one directly-exporting industry, this sample is over 12 times larger and includes non-manufacturing plants. The extensive-margin (exit) finding aligns with Asquith et al. (2019).
What are the policy implications and their scope conditions?
Because the indirect channel propagates the China shock to plants with no direct exposure - including non-manufacturing establishments - and operates through permanent establishment exit, the documented economic, social, and political consequences of import competition may be even larger than estimates ignoring within-firm networks suggest. The authors stop short of quantifying the channel against other channels (supply chains, financial networks, migration, local adjustment) and note that designing optimal trade/industry policy under within-firm linkages requires a full structural model, which they leave to future work. Scope: results pertain to U.S. multisector firms with at least one manufacturing plant over 1991-2007, which cover three-quarters of manufacturing but only about 20-25% of overall employment, so sector-level estimates are less precise once non-manufacturing is included.
Why does the entry margin matter and what is found?
Establishment exit is more permanent than intensive-margin cuts, so it signals persistent damage. The baseline decomposition lacks an entry margin; the authors augment the sample with post-1991 entrants (assigning arc-growth of 2, weighting by midpoint employment). The exit margin remains highly significant and accounts for the overall effect, while the entry margin is quantitatively small and statistically insignificant - multisector firms do not adjust to the China shock by opening new plants.
What is found at the sector level and why does it matter?
To rule out that laid-off workers are simply rehired by other plants in the same industry, the authors define sector employment as total employment of all plants (including single-sector firms) and build a sector-level indirect shock weighting each other sector by its within-firm importance averaged across firms. For manufacturing, the indirect sector shock is large and significant at the 10% level (coefficient about -0.747), with the exit margin significant at 1% (about -0.371). Results are strongest for manufacturing and less precise when non-manufacturing is included, because the sample covers about three-quarters of manufacturing but only about 20% of overall employment. Spillovers thus survive aggregation.